Human Activity Recognition (HAR) systems are widely used in Industry 4.0 to ensure workers safety in hazardous zones. For this purpose, motion sensors, such as accelerometer and gyroscope, that are widely available on handheld PDA devices are utilized. The HAR system we use operates based on the sequential neural network model with four layers to identify the worker's activities (namely, walking, walking upstairs, walking downstairs, sitting). For analysis, we use a dataset of UCI machine learning repository, known as Human Activity Recognition Using Smartphones [1]}.
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